{"id":"W2745408025","doi":"10.1021/acssensors.7b00539","title":"August 2017: Two Years of Submissions","year":2017,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001050906,0.0001099098,0.0001762674,0.00002192996,0.0001976255,0.00006145488,0.0007151277,0.0001160805,0.001412108],"category_scores_gemma":[0.0008969466,0.0001172677,0.00007928479,0.000027908,0.000216315,0.00008763081,0.0002509342,0.000275687,0.0001147296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000369533,"about_ca_system_score_gemma":0.00008477961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002919638,"about_ca_topic_score_gemma":0.0000168651,"domain_scores_codex":[0.9989575,0.000009425448,0.00018091,0.0002258285,0.0003162785,0.0003101108],"domain_scores_gemma":[0.9981592,0.00007497641,0.0001645016,0.001344852,0.00008658965,0.0001698911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002687943,0.00009239489,0.02315043,0.0001153831,0.00007194874,0.0001755721,0.0002041574,0.00002746531,0.9565037,0.0003265291,0.01462551,0.004680035],"study_design_scores_gemma":[0.000738207,0.000008948516,0.007525959,0.0000699173,0.00002160742,0.00003177174,0.0001194451,0.0001040535,0.947997,0.0004488959,0.04272092,0.0002132358],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8196638,0.00002846131,9.868565e-7,0.0002628057,0.00004303813,0.00002534959,0.00002963187,0.00003782163,0.1799081],"genre_scores_gemma":[0.9480336,0.0000442059,0.000200582,0.000009401873,0.0001690468,0.0000032666,0.00001149298,0.0000220737,0.05150636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1284017,"threshold_uncertainty_score":0.9995008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04466248383042012,"score_gpt":0.3367050840865335,"score_spread":0.2920426002561134,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}